Call for papers

KDMiLe 2024

The Symposium on Knowledge Discovery, Mining and Learning (KDMiLe) aims at integrating researchers, practitioners, developers, students, and users to present their research results, discuss ideas, and exchange techniques, tools, and practical experiences – related to the Data Mining and Machine Learning areas.

KDMiLe originated from WAAMD (Workshop em Algoritmos e Aplicações de Mineração de Dados) that occurred during five years – 2005 to 2009 – as a Workshop of the Brazilian Symposium on Databases (SBBD). Since 2013, KDMiLe has been organized alternatively in conjunction with the Brazilian Conference on Intelligent Systems (BRACIS) and the Brazilian Symposium on Databases (SBBD).

This year, 2024, in its twelfth edition, KDMiLe will be held in Belém, Pará, from 17-21 November, in conjunction with the Brazilian Conference on Intelligent Systems (BRACIS). This year KDMiLe is being organized by Universidade Federal do Pará.

SUBMISSION & PRESENTATION GUIDELINES

• Papers may be written in Portuguese or English, but the title, the abstract, and the keywords must be written in English.
• Submissions are reviewed following a single blind review process, i.e., you do not need to hide authors’ names and affiliations.
• The manuscript must not exceed 8 pages. Papers exceeding this limit will be automatically rejected without being reviewed by the Program Committee.
• Papers must be submitted in PDF format. Formats other than PDF will NOT be accepted.
• Latex template available here.
• Papers must be submitted through JEMS.

Papers submitted to KDMiLe must not have been simultaneously submitted to any other forum (conference or journal), nor should they have already been published elsewhere. The acceptance of a paper implies that at least one of its authors will register for the symposium to present it.

Submitted papers will be reviewed based on originality, relevance, technical soundness, and clarity of presentation.

Accepted papers will be published electronically in the KDMiLe proceedings. A preliminary version of the proceedings, including all the accepted papers, will be available to the symposium attendees.

In all past editions, authors of selected papers accepted for presentation in KDMiLe have been invited to submit extended and revised versions of these papers to a special issue of JIDM (Journal of Information and Database Management). This year, we intend to follow this same policy of encouraging the best submissions with publication in an international journal.

Plenary Speakers

Title: Advancing Neural Model Design: Optimisation Across Machine Learning Tasks

Abstract: Machine Learning (ML) is a subset of Artificial Intelligence (AI) dedicated to constructing data-driven parametric predictive models. This presentation highlights the critical role of optimisation in ML, encompassing various phases of the modelling process. It explores three essential ML tasks: 1) selecting model variables through feature selection; 2) determining model parameters via model training; and 3) designing model structures, particularly through neural architecture search. All these tasks can be interpreted as aspects of neural model design, where the primary objective is to achieve the highest accuracy in ML model predictions. The speaker will present recent research addressing each of these challenges, offering insights into advanced optimisation techniques within the context of ML.

Bio : Ferrante Neri received his Laurea and Ph.D. degrees in Electrical Engineering from the Politecnico di Bari, Italy, in 2002 and 2007, respectively. He also obtained a second Ph.D. in Scientific Computing and Optimization, and a D.Sc. in Computational Intelligence from the University of Jyväskylä, Finland, in 2007 and 2010, respectively. Between 2009 and 2014, he was an Academy Research Fellow with the Academy of Finland, leading the project on Algorithmic Design Issues in Memetic Computing. He served at De Montfort University, Leicester, UK, from 2012 to 2019 and at the University of Nottingham, UK, from 2019 to 2022. Since 2022, he has been a Full Professor of Machine Learning and Artificial Intelligence at the University of Surrey, Guildford, and the Head of the Nature Inspired Computing and Engineering (NICE) Research Group. Additionally, he holds the title of Jiangsu Distinguished Professor at Nanjing University of Information Science and Technology. His research focuses on metaheuristic optimisation with applications in machine learning.

 

Profa. Mariza Ferro

Title: Inteligência Artificial e a {In}Sustentabilidade do Atual Paradigma de Desenvolvimento                                                                                             

Abstract: Os benefícios da Inteligência Artificial (IA) são visíveis em muitos domínios e há evidências de que ela pode ser uma habilitadora para alcançarmos a maioria dos Objetivos do Desenvolvimento Sustentável (ODS). Por outro lado, tem se debatido sobre os impactos negativos da IA e seu possível papel inibidor para o sucesso destes mesmos ODS. Muitos destes impactos negativos decorrem do paradigma de desenvolvimento dos atuais modelos de IA que se baseiam na ideia de “quanto mais melhor”. Assim, os requisitos computacionais e de dados para treinamento desses modelos são enormes, e consequentemente, o consumo de energia e de água. Porém, estes requisitos não trazem apenas implicações para a sustentabilidade do ponto de vista ambiental, mas também econômico e social, com profundas consequências políticas e favorecimento de algumas regiões demográficas em detrimento de outras. Nesta palestra serão apresentados os elementos técnicos computacionais deste atual paradigma de desenvolvimento, explorando qual a origem dos custos negativos da IA e refletindo sobre caminhos para o desenvolvimento de uma IA sustentável, em benefício das pessoas e do planeta e para que estes benefícios sejam amplamente compartilhados.

Bio : Currently works as Artificial Intelligence professor at Instituto de Computação – Universidade Federal Fluminense (UFF). Coordinator of the Reference Group for Ethical and Trustworthy AI and coordinator of the Consortium of Ethics for Public Policies on Artificial Intelligence for Latin America and the Caribbean (EticALIA). Researcher supported by the Serrapilheira Institute and Faperj. Ph.D. in Computational Modeling at the National Laboratory of Scientific Computing (LNCC) and M.Sc. in Computer Science from Universidade de São Paulo. Member of the Brazilian Computing Society (SBC) serving on the Education Committee for the 2023-2025 biennium. Member of the Research Ethics Committee of the Faculty of Medicine – UFF. Member of Association for Computing Machinery (ACM). Nomitaded to AI Connect II – U.S. Government Program Advancing Global Consensus on Trustworthy AI. Visiting researcher at INRIA – Bordeaux (2023-2024). Her research interests are Green AI, ML and Sustainability, including predicting extreme weather events; AI Ethics and AI for social Good.

PROGRAM COMITTEE

–   Alan Valejo (Universidade de São Carlos – UFSCar)

–   Alexandre Evsukoff (COPPE/UFRJ)

–   Alexandre Plastino (Universidade Federal Fluminense)

–   Ana Carolina Lorena (Instituto Tecnológico de Aeronáutica)

–   André Rossi (São Paulo State University – UNESP)

–   Anna Helena Reali Costa (Universidade de São Paulo)

–   Aurora Pozo (UFPR)

–   Bianca Zadrozny (IBM Research)

–   Bruno Nogueira (Universidade Federal de Mato Grosso do Sul)

–   Carlos Ferrero (Instituto Federal de Santa Catarina)

–   Carlos Eduardo Pantoja (CEFET/RJ)

–   Claudia Justel (Instituto Militar de Engenharia)

–   Daniel Martins (IME)

–   Daniel Salles Civitarese (IBM Research)

–   Daniela Barreiro Claro (Federal University of Bahia)

–   Dayse de Almeida (Universidade Federal de Catalão – UFCAT)

–   Debora Medeiros (Universidade Federal do ABC)

–   Diego Carvalho (CEFET/RJ)

–   Diego Furtado Silva (Universidade de São Paulo)

–   Edson Gomi (University of São Paulo)

–   Edson Matsubara (Fundação Universidade Federal de Mato Grosso do Sul)

–   Eduardo Ogasawara (CEFET/RJ)

–   Elaine Sousa (University of Sao Paulo)

–   Erick Florentino (Instituto Militar de Engenharia)

–   Eugênio Silva (UERJ – Universidade do Estado do Rio de Janeiro)

–   Fabio Lobato (Universidade Federal do Oeste Pará)

–   Fabio Porto (LNCC)

–   Fabrício Pereira (Universidade Federal do Estado do Rio de Janeiro – UNIRIO)

–   Fábio Cozman (USP – Politécnica)

–   Fellipe Duarte (Universidade Federal Rural do Rio de Janeiro)

–   Fernanda Baião (PUC-Rio)

–   Francisco De Carvalho (Centro de Informática – CIn/UFPE)

–   Gabriel Machado (Pontifícia Universidade Católica do Rio de Janeiro)

–   Gustavo Guedes (CEFET/RJ)

–   Helena Caseli (UFSCar)

–   Humberto Razente (Universidade Federal de Uberlandia)

–   Jonice Oliveira (Universidade Federal do Rio de Janeiro – UFRJ)

–   Jonnathan Carvalho (Instituto Federal de Educação, Ciência e Tecnologia Fluminense)

–   Jorge Soares (CEFET/RJ)

–   José Luiz Neves Voltan (Instituto Militar de Engenharia)

–   Julio Duarte (Instituto Militar de Engenharia)

–   Julio Nievola (PUCPR)

–   Karin Becker (UFRGS)

–   Kate Revoredo (Humboldt-Universität zu Berlin)

–   Leandro Miranda (Blueshift)

–   Leonardo Emmendörfer (Universidade Federal de Santa Maria)

–   Leonardo Tomazeli Duarte (University of Campinas)

–   Leonardo F. R. Ribeiro (Amazon)

–   Lucas Bastos Germano (Instituto Militar de Engenharia)

–   Luis Zárate (Pntifícia Universidade Católica de Minas Gerais)

–   Luiz Martins (Universidade Federal de Uberlândia)

–   Luiz Henrique de Campos Merschmann (Universidade Federal de Lavras)

–   Marcela Ribeiro (Universidade Federal de São Carlos – UFSCar)

–   Marcelino Pereira (UERN)

–   Marcelo Albertini (Federal University of Uberlandia)

–   Marcelo Finger (USP/IME)

–   Marcelo Manzato (University of Sao Paulo)

–   Marcos Bedo (Universidade Federal Fluminense)

–   Maria Camila Nardini Barioni (UFU)

–   Mariza Ferro (Universidade Federal Fluminense)

–   Marlo Souza (Universidade Federal da Bahia – UFBA)

–   Mauri Ferrandin (Universidade Federal de Santa Catarina – UFSC)

–   Mário Benevides (Universidade Federal Fluminense – UFF)

–   Murillo Carneiro (Federal University of Uberlândia)

–   Murilo Loiola (Universidade Federal do ABC)

–   Murilo Naldi (Universidade Federal de São Carlos)

–   Nuno David (ISCTE)

–   Pablo Rangel (Instituto de Pesquisas da Marinha)

–   Paula Costa (UNICAMP)

–   Paulo Freire (Fundação de Apoio à Escola Técnica do Estado do Rio de Janeiro)

–   Paulo Quaresma (Universidade de Évora)

–   Paulo Henrique Pisani (Universidade Federal do ABC – UFABC)

–   Paulo T. Guerra (Federal University of Ceará)

–   Priscila Lima (UFRJ)

–   Rafael Bordini (PUCRS)

–   Rafael Gomes Mantovani (Federal Technology University of Paraná, Campus of Apucarana)

–   Renato Tinos (USP)

–   Ricardo Cerri (Universidade de São Paulo)

–   Ricardo Marcacini (ICMC/USP)

–   Ricardo Rios (Universidade Federal da Bahia)

–   Ricardo Augusto Souza Fernandes (Federal University of São Carlos)

–   Richard Gonçalves (UNICENTRO)

–   Roberto Santana (University of the Basque Country)

–   Rodrigo Kishi (Universidade Federal de Mato Grosso do Sul)

–   Ronaldo Prati (Universidade Federal do ABC)

–   Roseli Ap. Francelin Romero (USP-SC)

–   Rosiane de FreitasR (IComp/UFAM)

–   Sílvio Cazella (UFCSPA)

–   Silvia Botelho (FURG)

–   Stefano Suraci (Instituto Militar de Engenharia)

–   Tatiane Nogueira (Federal University of Bahia)

–   Thiago Pardo (USP/ICMC)

–   Tiago Tavares (Insper)

–   Vasco Furtado (Universidade de Fortaleza – UNIFOR)

–   Wagner Meira Jr. (UFMG)